1. LiDAR and EFI Data within BCTS

2. Presentation Outline Current State and LiDAR/EFI coverage
Decision matrix
Derivatives or end products
Current uses of the data
Benefits

3. Current State 11 out of 12 Business Areas have LiDAR data
3 of those BA’s currently have EFI data
First LiDAR acquisition in 2010 in Port McNeill (TST), they have the most experience using the data
Approximately 25% LiDAR coverage of Business Areas to date, approx 4.1 million ha (2016 hectares not all delivered)
334,000 ha of EFI planned by end of 2017 (approx)

4. Current LiDAR coverage

5. Current EFI Coverage

6. Acquisition Summary – All Data
BCTS LiDAR Acquisition 2010 – Present
Business Area
2010
2012
2013
2014
2015
2016
2017
Grand Total
TBA
73301
TCC
516226
99778
616004
TCH
2344
3387
14787
360938
50000
431456
TKA
64312
69726
267347
401385
TKO
37353
284877
688124
TOC
72139
95217
296596
463951
TPG
445892
147046 
592941
TSG
2290
5755
44635
130843
76193
258045
TSK
45985
TSN
27312
TST
4318
61483
23095
20999
71564
181459
580671
28850
225503
126193

7. LiDAR Summary by Operating Area (as of March 6, 2017)

8. Percentage of LiDAR Coverage within Operating Areas to end of 2017

9. Percentage of EFI Coverage within Operating Areas to end of 2017

10. Why did BCTS acquire LiDAR/EFI?
To aid in meeting BCTS’s Mandate of collecting data from Auctioned Timber Sales to set the stumpage rate for all Timber harvested from Crown lands by other Licensees.
More accurate information for remote, high cost areas
LiDAR provides more accurate canopy level information than VRI polygons
LiDAR provides more accurate terrain information than TRIM
LiDAR and EFI allow for land based information to be operationalized for planning and engineering ie better Total Chance Planning = isolating less timber
VRI is more suited for higher level planning and Timber Supply Modelling

11. Why did BCTS acquire LiDAR/EFI? (con’t)
LiDAR/EFI is increasing efficiency in all phases of planning
More time is now allocated to office engineering to maximize field work productivity, less rework/pulling out ribbons, less field work in general
Better decisions are being made earlier in the planning process, more efficient, cost savings and evaluation of road options using RoadEng Optimal
EFI has allowed easier identification of potential Timber Sale quality blocks

12. Phase 1 Recce Example

13. Crown height data

14. RoadEng Software

15. Creating the Optimum Grade

16. Deflection Lines

17. Deflection Line Map

18. Deflection Line in 3D

19. Lidar/EFI Data Uses
The EFI was used for the Total Chance Plan of the Holberg area
Merchantable/saleable stand identification
Quantifying the impacts of proposed WHAs using the volume impacted converted to $
RoadEng, Terrain and Location road alignment and block layout by field engineers, regional engineering staff and contractors
Mule Deer Winter Range Modelling from the CHM, canopy closure and canopy complexity
Many other modelling potential ie Marbled Murrelet, Goshawk

20. EFI Derived Volumes

21. Crown Height Model Canopy Closure/Structure

22. Net Merch Volume

23. LiDAR vs EFI Tree Heights

24. Hydrologic Streams and Basins

25. Stream gradients

26. Tree Top Analysis

27. Harvest Block Cut into DSM

28. What are the Benefits of LiDAR/EFI
LiDAR/EFI data identifies canopy level attributes better than VRI, optics are better for prioritizing/planning Timber Sale level blocks
LiDAR data easily integrates with existing GIS and Forest Engineering software, helps to maximize Return on Investment
Better crown height and ground information available in the planning phase allows better decisions and less rework
Potentially less road building as multiple deflection line options can be compared easily beforehand, lower engineering costs per TSL
Less field work overall should result in improved safety for workers and a reduction in engineering costs

29. Benefits (con’t)
More accurate Visual Impact Assessments, using better ground and tree heights, potential to harvest more in visually constrained areas
Better utilisation of the timber resource and land base with less chance of isolating timber
Ability to generate hydrologic streams, reach breaks and barriers to fish passage to identify optimum bridge and culvert crossing locations, better road reactivation data
Better able to manage for non timber resources ie crown closure for Mule Deer winter range habitat.
Potential to solve the aging workforce issue

30. Questions?